Note: The job is a remote job and is open to candidates in USA. Bollinger Shipyards is seeking an experienced Senior Data Engineer to strengthen its enterprise data foundation. The role designs, builds, and supports Azure-based data pipelines and solutions integrating operational systems to deliver trusted data for analytics, forecasting, artificial intelligence, and enterprise decision-making.
Responsibilities
- Design, develop, test, and maintain scalable enterprise data pipelines
- Build ingestion processes integrating Oracle ERP, Finesse, MES/PLM, historical proposal data, and other enterprise systems
- Implement Bronze, Silver, and Gold data layers within the enterprise Azure data platform
- Develop transformations and curated datasets supporting analytics, dashboards, forecasting, and AI
- Design and implement data models optimized for analytical and operational use cases
- Develop data-quality checks, reconciliation processes, monitoring, and alerting
- Troubleshoot data issues and perform root-cause analysis across source systems and pipelines
- Optimize pipelines, SQL, and data models for performance, scalability, and reliability
- Implement automated testing, source control, CI/CD, and DataOps practices
- Apply enterprise architecture, security, governance, and data-management standards
- Work with Data Governance to ensure appropriate handling of sensitive and regulated data
- Partner with Analytics and AI teams to provide reliable, production-ready datasets
- Participate in design and code reviews and mentor less-experienced data engineers
- Contribute to enterprise data engineering standards, patterns, and reusable components
Skills
- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field
- 5+ years of relevant data engineering experience
- Strong hands-on SQL skills
- Experience designing and developing production ETL/ELT pipelines
- Experience with Azure data technologies, such as Microsoft Fabric, Azure Data Factory, Synapse, Databricks, or equivalent platforms
- Experience with data warehousing and dimensional/data modeling
- Experience integrating ERP, operational, and enterprise application data
- Experience developing reliable, scalable production data solutions
- Strong understanding of data quality, performance, and production support
- SQL and Python/PySpark
- Microsoft Fabric, Azure Data Factory, Synapse, Databricks, or related Azure technologies
- ETL/ELT and enterprise data integration
- Data warehousing and dimensional modeling
- Bronze / Silver / Gold medallion architecture
- Batch and incremental data processing
- Data quality, reconciliation, and observability
- Git, CI/CD, automated testing, and DataOps practices
- Experience with Oracle ERP, IFS, MES, PLM, or other enterprise operational systems is preferred
- Experience in manufacturing, industrial, shipbuilding, engineering, or other complex operational environments is preferred
Company Overview
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